Exam AWS Certified Machine Learning - Specialty topic 1 question 62 discussion

A is correct. Kinesis Data Analytics can use lamda to convert GZIP and can run SQL on the converted data. https://aws.amazon.com/about-aws/whats-new/2017/10/amazon-kinesis-analytics-can-now-pre-process-data-prior-to-running-sql-queries/

A is correct: https://aws.amazon.com/about-aws/whats-new/2017/10/amazon-kinesis-analytics-can-now-pre-process-data-prior-to-running-sql-queries/ "To get started, simply select an AWS Lambda function from the Kinesis Analytics application source page in the AWS Management console. Your Kinesis Analytics application will automatically process your raw data records using the Lambda function, and send transformed data to your SQL code for further processing. Kinesis Analytics provides Lambda blueprints for common use cases like converting GZIP ..."

Use Amazon Kinesis Data Analytics if you need SQL-based processing and advanced analytics capabilities for streaming data. Use Amazon Kinesis Data Firehose if your primary requirement is to deliver, transform, and load streaming data into various AWS destinations with simplified configurations, but not for SQL-based processing.

If gaining real-time insights involves complex analytics or custom processing, Amazon Kinesis Data Analytics with AWS Lambda is likely a more suitable choice. If the requirements can be met with simpler data transformations, Amazon Kinesis Data Firehose might provide a more straightforward and potentially lower-latency solution. In other words, if this data is in GZIP files and the processing requirements are relatively simple, Amazon Kinesis Data Firehose might be a more straightforward and efficient choice. GZIP files typically contain compressed data, and if our primary objective is to ingest, transform, and load this data into other AWS services for real-time insights, Kinesis Data Firehose provides a managed and streamlined solution that can handle GZIP compression.

A is correct, why D xiyarsan sen?

A is correct

"allow the use ohttps://www.examtopics.com/exams/amazon/aws-certified-machine-learning-specialty/view/13/#f SQL to query the stream with the LEAST latency?" Well, the only solution that presents SQL query is (A). It's a description of KDA.

the term "lease latency" is the the hidden point. with Glue we can have near real-time but Kinesis data analytics will give you real-time transformation with internal lambda

A is correct, with KDA you can run sql queries in the data during the streaming (real-time SQL queries).

D. Amazon Kinesis Data Firehose to transform the data and put it into an Amazon S3 bucket would be the best solution for allowing the use of SQL to query the stream with the least latency. Amazon Kinesis Data Firehose can be configured to transform the data before writing it to Amazon S3 in real-time. Once the data is in S3, it can be queried using SQL with Amazon Athena, which is a serverless query service that allows running standard SQL queries against data stored in Amazon S3. This approach provides the lowest latency compared to other options and requires minimal setup and maintenance.

A is correct.

And somehow "transformation" is added to the answer as a requirement when it clearly was not part of the requirement from the question.

AAAAAAA

what about "LEAST latency"?

A is correct. you can pre-process data prior to running SQL queries with Kinesis Data Analytics and Lambda (more or less) is always a best practice :)

Answer is B. Kinesis Data Analytics does not do any transformation, it is only for querying. Glue ETL can have scripts that can transform the data